http://precedings.nature.com/tags/ontology%20engineering Recently posted documents tagged with 'ontology engineering' Nature Publishing Group en Nature Precedings http://precedings.nature.com/images/header_logo.gif http://precedings.nature.com http://dx.doi.org/10.1038/npre.2009.3753.1 The ACGT project which aims to foster the sharing of research result from both, clinical and molecular research for the benefit of cancer patients uses ontology-driven semantic services. One novelty ACGT provides is a tool named ObTiMA which allows to build questionnaires directly from the ACGT Master Ontology. This will facilitate the process of creating Case Report Forms. Furthermore, the clinical data collected is already annotated in the terms of the ontology. http://dx.doi.org/10.1038/npre.2009.3753.1 Mon, 14 Sep 2009 08:52:16 UTC Ontology-based Trial Management System (ObTiMA) doi:10.1038/npre.2009.3753.1 2009-09-14 Mathias Brochhausen Nature Precedings 2009-09-14T08:52:16Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3479.1 Over the past few years the number of bio-ontologies has rapidly increased. The evaluation of ontologies has long been a problematic issue. The growing number of ontologies makes the need for a strategy for evaluating quality more urgent. We propose a framework for evaluating the quality of bio-ontologies. This framework is inspired by a well-known software quality standard, which has been adapted to the needs of ontology evaluation. An example of how to use the framework, comparing two versions of the Open Biomedical Ontologies’ Cell Type Ontology, is included as an illustration. http://dx.doi.org/10.1038/npre.2009.3479.1 Tue, 28 Jul 2009 14:26:47 UTC A Quality Evaluation Framework for Bio-Ontologies doi:10.1038/npre.2009.3479.1 2009-07-28 Jesualdo Tomas Fernandez-Breis Nature Precedings 2009-07-28T14:26:47Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3478.1 Over the past few years the number of bio-ontologies has rapidly increased. The evaluation of ontologies has long been a problematic issue. The growing number of ontologies makes the need for a strategy for evaluating quality more urgent. We propose a framework for evaluating the quality of bio-ontologies. This framework is inspired by a well-known software quality standard, which has been adapted to the needs of ontology evaluation. An example of how to use the framework, comparing two versions of the Open Biomedical Ontologies’ Cell Type Ontology, is included as an illustration. http://dx.doi.org/10.1038/npre.2009.3478.1 Mon, 27 Jul 2009 20:25:59 UTC A Quality Evaluation Framework for Bio-Ontologies doi:10.1038/npre.2009.3478.1 2009-07-27 Jesualdo Tomas Fernandez-Breis Nature Precedings 2009-07-27T20:25:59Z Presentation Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/3231/version/1 This paper addresses two research questions: “How should a well-engineered methodology facilitate the development of ontologies within communities of practice?” and “What methodology should be used?” If ontologies are to be developed by communities then the ontology development life cycle should be better understood within this context. This paper presents the Melting Point (MP), a proposed new methodology for developing ontologies within decentralized settings. It describes how MP was developed by taking best practices from other methodologies, provides details on recommended steps and recommended processes, and compares MP with alternatives. The methodology presented here is the product of direct first-hand experience and observation of biological communities of practice in which some of the authors have been involved. The Melting Point is a methodology engineered for decentralised communities of practice for which the designers of technology and the users may be the same group. As such, MP provides a potential foundation for the establishment of standard practices for ontology engineering. http://precedings.nature.com/documents/3231/version/1 Fri, 08 May 2009 09:47:22 UTC Developing ontologies in decentralised settings hdl:10101/npre.2009.3231.1 2009-05-08 Frank Gibson Nature Precedings 2009-05-08T09:47:22Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/2027/version/2 Increasingly, in data-intensive areas of the life sciences, experimental results are being described in algorithmically useful ways with the help of ontologies. Such ontologies are authored and maintained by scientists to support the retrieval, integration and analysis of their data. The proposition to be defended here is that ontologies of this type – the Gene Ontology (GO) being the most conspicuous example – are a part of science. Initial evidence for the truth of this proposition (which some will find self-evident) is the increasing recognition of the importance of empirically-based methods of evaluation to the ontology develop¬ment work being undertaken in support of scientific research. Ontologies created by scientists must, of course, be associated with implementations satisfying the requirements of software engineering. But the ontologies are not themselves engineering artifacts, and to conceive them as such brings grievous consequences. Rather, ontologies such as the GO are in different respects comparable to scientific theories, to scientific databases, and to scientific journal publications. Such a view implies a new conception of what is involved in the author¬ing, maintenance and application of ontologies in scientific contexts, and therewith also a new approach to the evaluation of ontologies and to the training of ontologists. http://precedings.nature.com/documents/2027/version/2 Wed, 16 Jul 2008 15:49:38 UTC Ontology (Science) hdl:10101/npre.2008.2027.2 2008-07-16 Barry Smith Nature Precedings 2008-07-16T15:49:38Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2008.2027.1 Increasingly, in data-intensive areas of the life sciences, experimental results are being described in algorithmically useful ways with the help of ontologies. Such ontologies are authored and maintained by scientists to support the retrieval, integration and analysis of their data. The proposition to be defended here is that ontologies of this type – the Gene Ontology (GO) being the most conspicuous example – are a part of science. Initial evidence for the truth of this proposition (which some will find self-evident) is the increasing recognition of the importance of empirically-based methods of evaluation to the ontology development work being undertaken in support of scientific research. The ontologies created by scientists must, of course, be associated with implementations satisfying the requirements of software engineering. But these ontologies are not themselves engineering artifacts, and to conceive them as such brings grievous consequences. Rather, we shall argue, ontologies such as the GO are comparable to scientific theories, to scientific databases, or to scientific journal publications. Such a view implies a radically new conception of what is involved in the authoring, maintenance and application of ontologies in scientific contexts, and therewith also a radically new approach to the evaluation of ontologies and to the training of ontologists. http://dx.doi.org/10.1038/npre.2008.2027.1 Tue, 01 Jul 2008 16:43:36 UTC Ontology (Science) doi:10.1038/npre.2008.2027.1 2008-07-01 Barry Smith Nature Precedings 2008-07-01T16:43:36Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/